Scientific.Statistics

Package Scientific :: Package Statistics |
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# Package Statistics

Basic monovariate statistics

Submodules
Scientific.Statistics.Histogram: Standard and weighted histograms

Functions
number |
average(data) Mean (average value, first moment) |
number |
correlation(data1, data2) Calculates the correlation coefficient between two data sequences |
number |
kurtosis(data) Kurtosis (fourth normalized moment) |
number |
mean(data) Mean (average value, first moment) |
number |
median(data) Median |
mode(data) |
number |
moment(data, order, about=None, theoretical=1) Calculate the moments of the distribution corresponding to a set of data |
number |
normalizedMoment(data, order) Calculate the normalized moments of the distribution corresponding to a set of data. |
number |
skewness(data) Skewness (third normalized moment) |
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standardDeviation(data) Standard deviation |
number |
variance(data) Variance (second moment) |
`tuple` of two elements |
weightedMean(data, sigma) Weighted mean of a sequence of numbers with given standard deviations |

Function Details

### average(data) |
Mean (average value, first moment) Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the mean of the number sequence

### correlation(data1, data2) |
Calculates the correlation coefficient between two data sequences Parameters: `data1` (`Numeric.array` or `list`) - first data sequence `data2` (`Numeric.array` or `list`) - second data sequence of length identical to data1 Returns: number the correlation coefficient between data1 and data2 Raises: `ValueError` - if data1 and data2 have different lengths

### kurtosis(data) |
Kurtosis (fourth normalized moment) Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the kurtosis of the number sequence

### mean(data) |
Mean (average value, first moment) Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the mean of the number sequence

### median(data) |
Median Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the median of the number sequence

### moment(data, order, about=None, theoretical=1) |
Calculate the moments of the distribution corresponding to a set of data Parameters: `data` (`Numeric.array` of numbers) - a sequence of data points `order` (`int`) - the order of the moment to be calculated `about` (number) - the center of the distribution. If `None`, use the mean value as the center. `theoretical` - for internal use Returns: number the moment of the given order about the specified center

### normalizedMoment(data, order) |
Calculate the normalized moments of the distribution corresponding to a set of data. Normalization means division by the n-th power of the standard deviation. Parameters: `data` (`Numeric.array` of numbers) - a sequence of data points `order` (`int`) - the order of the moment to be calculated Returns: number the normalized moment of the given order

### skewness(data) |
Skewness (third normalized moment) Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the skewness of the number sequence

### standardDeviation(data) |
Standard deviation Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the standard deviation of the number sequence

### variance(data) |
Variance (second moment) Parameters: `data` (`list` or `Numeric.array`) - a sequence of numbers Returns: number the variance of the number sequence

### weightedMean(data, sigma) |
Weighted mean of a sequence of numbers with given standard deviations Parameters: `data` (`list` or `Numeric.array`) - a sequence of measurements `sigma` (`list` or `Numeric.array`) - a sequence of corresponding standard deviations Returns: `tuple` of two elements the weighted mean and corresponding standard deviation